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EMG functions and classification methods for prosthesis control - Joseph Betthauser

Version 1.0(83.3 KB) by Joseph Betthauser
EMG DSP functions, classifiers, and miscellaneous
5.0
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Updated24 Jun 2018

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I am re-upping my functions folder for the newcomers to EMG signal processing, prosthesis control, and classification. Some are designed to make commonly-used EMG DSP and classification procedures easy to perform, and some are based on my research. Most, if not all, have been optimized for speed and efficient data management. Description on how to use folder for classification in MATLAB is detailed with useable "cut and paste" code in the word file.
There are other useful tools contained in the folders such as k-means dictionary reduction, k-gmm clustering, optimal channel/feature subset selection, offline and online versions of useful classifiers, useful distance/similarity metrics, and cubic interpolation for "up-sampling" or down-sampling.

Cite As

Joseph Betthauser (2023).EMG functions and classification methods for prosthesis control - Joseph Betthauser(//www.tatmou.com/matlabcentral/fileexchange/67821-emg-functions-and-classification-methods-for-prosthesis-control-joseph-betthauser), MATLAB Central File Exchange. Retrieved.

MATLAB Release Compatibility
Created with R2017b
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emg_functions/classify_offline/

emg_functions/classify_offline/EASRC utilities/

emg_functions/classify_online/

emg_functions/dictionary_compression/

emg_functions distance_measures /

emg_functions/emg_dsp_functions/

emg_functions/feature_selection/

emg_functions/image_processing/

emg_functions/performance_metrics/

Version Published Release Notes
1.0

removed some optimal features selectors because they were incomplete versions of the final design: JLB_featureSelect4()